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Enquire- Modern era of AI
- Role of Machine learning & Deep Learning in AI
- Hardware for AI (CPU vs. GPU vs. FPGA)
- Software Frameworks for AI & Deep Learning
- Key Industry applications of AI
- What are the Limitations of Machine Learning?
- What is Deep Learning?
- Advantage of Deep Learning over Machine learning
- Reasons to go for Deep Learning
- Real-Life use cases of Deep Learning
- Overview of important python packages for Deep Learning
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- Deep Learning with Python
Deep Learning with Python
BY
Analytixlabs
Develop your skills associated with aspects of deep learning along with TensorFlow and Keras utilizing the Python medium with deep learning with python course.
Online
150 Hours
₹ 25,000
Inclusive of GST
Quick facts
| particular | details | ||
|---|---|---|---|
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Medium of instructions
English
|
Mode of learning
Self study, Virtual Classroom
+1 more
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Mode of Delivery
Video and Text Based
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Frequency of Classes
Weekdays, Weekends
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Course overview
The deep learning with python online course is developed and offered by the online education provider Analytixlab for the students who wish to upskill themselves with the deep learning skills and technologies that drive state-of-the-art applications in the domain of artificial intelligence.
The course is scheduled for the candidates with the knowledge of fundamentals of data science and Python programming language and will take a hundred and thirty hours to complete the program.
The course training consists of twenty classes and the students are allowed to work with ten assignments and projects to exhibit the theoretical knowledge and concepts gained during the exploration of the artificial intelligence and deep learning domain in data science.
The deep learning with python training enables the students to gain expertise in deep learning and the candidates are provided with a dual certification by Analytixlab partnered with the International Business Machines Corporation and continuous support in finding job opportunities.
The highlights
- Online mode
- Interactive virtual learning
- Self-paced learning
- Demo session
- Student loan
- Dual certification
- Career guidance
Program offerings
- Course videos
- Recordings
- Case studies
- Projects
- Assignments
- Exercises
- Demo session
- Student loan
- Placement support
- Doubts resolution
- Course completion certificate.
Course and certificate fees
Fees information
₹ 25,000
(Inclusive of GST) Deep Learning with Python fee structure
| Heads | Amount in INR (exclusive of taxes) |
Classroom & Bootcamp | Rs. 30000 + taxes |
Fully Interactive Live Online | Rs. 30000 + taxes |
Blended eLearning | Rs. 25000 + taxes |
certificate availability
Yes
certificate providing authority
Analytixlabs
Eligibility criteria
Data science
Python
The students applying for the deep learning with python program should have a fundamental knowledge of data science with the programming language Python.
Certificate qualifying details
- The candidates will have to complete the projects and assignments without any plagiarism involved for evaluation within one year after the course begins to receive the course completion certificate from the leading data science institute Analytixlab.
- Those who wish to receive the dual certification must complete the projects and assignments along with the MCQ test for which two attempts are provided to clear within six months after the training began.
What you will learn
Knowledge of deep learning
Machine learning
Data science knowledge
Knowledge of artificial intelligence
Knowledge of python
Programming skills
The deep learning with python online syllabus is framed for students to learn about the fundamentals of deep learning and the methods to construct neural networks. The course also enables the students to gain an understanding to work with projects in artificial intelligence based on deep learning techniques combined with the tools of TensorFlow and Keras. Deep learning with python includes case studies based on computer vision, data processing of text, processing of images, speech analytics which is speech to text or voice tonality, and Internet of things(IoT).
Who it is for
The deep learning with python classes is for experts in the domain of analytics and data science who are interested in developing their skills in gaining hands-on experience with the execution of the techniques of artificial intelligence and deep learning with TensorFlow and Keras frameworks.
Admission details
The course admission for the deep learning with Python online course is done online through the Analytixlab website.
Step 1: Go to the course page of deep learning with the python program on the official website of Analytixlab.
Step 2: Choose your preferred mode of learning the course.
Step 3: Fill in the relevant information and complete the registration.
Filling the form
In the registration form, the candidates are required to enter their names, phone numbers, email addresses, course name, and city names.
The syllabus
Introduction to AI and deep learning
Introduction to Artificial Intelligence (AI)
Introduction to Cloud Computing & Git
- Introduction to Google Colab
- What is Cloud Computing? Why it matters?
- Traditional IT Infrastructure vs. Cloud Infrastructure
- Cloud Companies (IBM, Microsoft Azure, GCP, AWS ) & their Cloud Services
- Use Cases of Cloud computing
- Overview of Cloud Deployment Models
- Implementation of ML/DL model in Cloud
- Introduction to git
- Basic git commands hands on
- Recap of Machine Learning
Artificial Neural Network
- Introduction to Artificial Neural Networks
- Hidden layers, hidden units
- Illustrate & Training a Perceptron
- Limitations of A Single Layer Perceptron
- Illustrate Multi-Layer Perceptron
- Activation function, Loss Functions
- Understand Forward & Back propagation – Using Example
- Regularization – Types of Regularization
- Normalization
- Different Optimization Technique - Gradient Descent
- Vanishing Gradient
- Batch in ANN - Batch Norm
Introduction to Keras and Pytorch
- How to compose Models in Keras
- Saving and Loading a model with Keras
- Using Tensor Board with Keras
- Intuitively building networks with Keras
- How to compose Models in Pytorch
- Saving and Loading a model with Pytorch
- Intuitively building networks with Pytorch
Computer Vision Applications ,Text Mining and Chatbot
Computer Vision and Applications
- History of Computer Vision & Application
- Introduction to Convolution
- Multichannel Convolution
- Advanced Convolution Operation
- Batch Norm & GAP
- Implementation of basic network in Keras
Convolution Neural Nets-Architecture-Implementation
- Understanding CNN Architecture
- Regularization
- Dropout
- Different Image Augmentation
- Different Learning Rates
- Activation function
- Implementation
Popular ImageNet Models & Transfer Learning
- Introduction to Transfer Learning
- AlexNet,
- VGGNet,
- Resnet,
- ResNext,
- Inception
Computer Vision-Object Detection-Classification-Localization-Object Segmentation
- Object Detection - Localization
- Concept of IOU
- YOLO Model Architecture & Implementation
Computer Vision-Object Segmentation
- Object segmentation & Applications
- RCNN/ Fast RCNN /Faster RCNN
Computer Vision-Face Detection & Recognition
- Face Detection
- Face Tracking
- Face Recognition
Computer Vision-GAN+Auto Encoders
- GAN
- Different GAN Network
- Auto Encoders
Sequential Data ,Language Models & Text Mining
Sequential Data, Language Models & Text Mining
- NLP vs. NLU vs. NLG
- Vectorization using Word Embedding's
- Word2vec and Glove
- RNN/ LSTM/ Bi-LSTM/ GRU
Attention and Introduction to Popular Language Models
- Transfer Learning in Langauge Models
- ULMFiT
- Transformer
- Google’s BERT
- Transformer-XL
- OpenAI’s GPT-2
- ELMo
Language Models-Applications
- Machine Translation
- Text Classification
- Text Segmentation
- Sentiment Analysis
Sequential Data-Time Series-Forecasting Using LSTM
- Sequential Data-Time Series-Forecasting Using LSTM
Build Your Own Chatbot
- Introduction to Chatbots
- How chatbots work
- Different Types of Chatbots (FAQ, Conversational)
- Building Conversational chatbots
Reinforcement Learning and AI Project Deployment in Cloud
Reinforcement Learning
- What is Reinforcement Learning
- Environment
- Agent
- Bellman Equation
- Plan
- Markov Process
- Plan vs Policy
- Q Learning
- Deep Q Learning
- Playing Games with Reinforcement Learning
Deployment and Inference
- Recap AWS Lambda
- Start Deploying model in AWS
- Inference in Html Webpage
AI Project Deployment in Cloud
- AI Project Deployment in Cloud
How it helps
Deep learning with python certification helps the students gain knowledge about the implementation of deep learning technologies in the artificial intelligence industry. The students are equipped with the skills of deep learning used for image processing, natural language processing, and generation for Chatbots along with deep learning modeling for the applications in artificial intelligence. The program on deep learning with python benefits the learners by providing their expertise in the concepts of supervised learning models, predictive modeling using analytics, and unsupervised learning models.
FAQs
Which data science institute offers the course on deep learning with python?
The online education provider Analytixlab has developed deep learning with a python program for the analytics experts.
How long will it take to finish the deep learning with python online course?
The online course will take 150 hours to complete the course.
How many classes, assignments, and projects does the deep learning with python curriculum include?
The course includes 20 classes with 10 projects and assignments for the students to implement their data science skills.
Does deep learning with python classes have a free demo session?
Yes, Analytixlab provides a demo session for the students to get a clear idea of the learning process.
Can I pay the deep learning with python course fee in installments?
Yes, you can pay the course fee in three installments.
